Overview

Dataset statistics

Number of variables27
Number of observations2366
Missing cells4
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory499.2 KiB
Average record size in memory216.1 B

Variable types

Numeric25
DateTime1
Categorical1

Alerts

df_index is highly correlated with Open and 16 other fieldsHigh correlation
Open is highly correlated with df_index and 16 other fieldsHigh correlation
High is highly correlated with df_index and 16 other fieldsHigh correlation
Low is highly correlated with df_index and 16 other fieldsHigh correlation
Close is highly correlated with df_index and 16 other fieldsHigh correlation
Adj Close is highly correlated with df_index and 16 other fieldsHigh correlation
Volume is highly correlated with df_index and 16 other fieldsHigh correlation
EMA_9 is highly correlated with df_index and 16 other fieldsHigh correlation
EMA_22 is highly correlated with df_index and 16 other fieldsHigh correlation
SMA_5 is highly correlated with df_index and 16 other fieldsHigh correlation
SMA_10 is highly correlated with df_index and 16 other fieldsHigh correlation
SMA_15 is highly correlated with df_index and 16 other fieldsHigh correlation
SMA_30 is highly correlated with df_index and 16 other fieldsHigh correlation
RSI is highly correlated with MACD and 1 other fieldsHigh correlation
MACD is highly correlated with RSI and 2 other fieldsHigh correlation
MACD_signal is highly correlated with RSI and 2 other fieldsHigh correlation
PriceDiff is highly correlated with Return and 2 other fieldsHigh correlation
Return is highly correlated with PriceDiff and 2 other fieldsHigh correlation
ma50 is highly correlated with df_index and 16 other fieldsHigh correlation
MA10 is highly correlated with df_index and 16 other fieldsHigh correlation
MA50 is highly correlated with df_index and 16 other fieldsHigh correlation
Shares is highly correlated with MACD and 1 other fieldsHigh correlation
Close1 is highly correlated with df_index and 16 other fieldsHigh correlation
Profit is highly correlated with PriceDiff and 2 other fieldsHigh correlation
wealth is highly correlated with df_index and 16 other fieldsHigh correlation
LogReturn is highly correlated with PriceDiff and 2 other fieldsHigh correlation
df_index is highly correlated with Open and 15 other fieldsHigh correlation
Open is highly correlated with df_index and 15 other fieldsHigh correlation
High is highly correlated with df_index and 16 other fieldsHigh correlation
Low is highly correlated with df_index and 15 other fieldsHigh correlation
Close is highly correlated with df_index and 15 other fieldsHigh correlation
Adj Close is highly correlated with df_index and 15 other fieldsHigh correlation
Volume is highly correlated with HighHigh correlation
EMA_9 is highly correlated with df_index and 15 other fieldsHigh correlation
EMA_22 is highly correlated with df_index and 15 other fieldsHigh correlation
SMA_5 is highly correlated with df_index and 15 other fieldsHigh correlation
SMA_10 is highly correlated with df_index and 15 other fieldsHigh correlation
SMA_15 is highly correlated with df_index and 15 other fieldsHigh correlation
SMA_30 is highly correlated with df_index and 15 other fieldsHigh correlation
RSI is highly correlated with MACDHigh correlation
MACD is highly correlated with RSI and 2 other fieldsHigh correlation
MACD_signal is highly correlated with MACD and 1 other fieldsHigh correlation
PriceDiff is highly correlated with Return and 2 other fieldsHigh correlation
Return is highly correlated with PriceDiff and 2 other fieldsHigh correlation
ma50 is highly correlated with df_index and 15 other fieldsHigh correlation
MA10 is highly correlated with df_index and 15 other fieldsHigh correlation
MA50 is highly correlated with df_index and 15 other fieldsHigh correlation
Shares is highly correlated with MACD and 1 other fieldsHigh correlation
Close1 is highly correlated with df_index and 15 other fieldsHigh correlation
Profit is highly correlated with PriceDiff and 2 other fieldsHigh correlation
wealth is highly correlated with df_index and 15 other fieldsHigh correlation
LogReturn is highly correlated with PriceDiff and 2 other fieldsHigh correlation
df_index is highly correlated with Open and 14 other fieldsHigh correlation
Open is highly correlated with df_index and 15 other fieldsHigh correlation
High is highly correlated with df_index and 15 other fieldsHigh correlation
Low is highly correlated with df_index and 15 other fieldsHigh correlation
Close is highly correlated with df_index and 15 other fieldsHigh correlation
Adj Close is highly correlated with df_index and 15 other fieldsHigh correlation
EMA_9 is highly correlated with df_index and 15 other fieldsHigh correlation
EMA_22 is highly correlated with df_index and 15 other fieldsHigh correlation
SMA_5 is highly correlated with df_index and 15 other fieldsHigh correlation
SMA_10 is highly correlated with df_index and 15 other fieldsHigh correlation
SMA_15 is highly correlated with df_index and 15 other fieldsHigh correlation
SMA_30 is highly correlated with df_index and 15 other fieldsHigh correlation
RSI is highly correlated with MACDHigh correlation
MACD is highly correlated with RSI and 2 other fieldsHigh correlation
MACD_signal is highly correlated with MACD and 1 other fieldsHigh correlation
PriceDiff is highly correlated with Return and 2 other fieldsHigh correlation
Return is highly correlated with PriceDiff and 2 other fieldsHigh correlation
ma50 is highly correlated with df_index and 15 other fieldsHigh correlation
MA10 is highly correlated with df_index and 15 other fieldsHigh correlation
MA50 is highly correlated with df_index and 15 other fieldsHigh correlation
Shares is highly correlated with MACD and 1 other fieldsHigh correlation
Close1 is highly correlated with df_index and 15 other fieldsHigh correlation
Profit is highly correlated with PriceDiff and 2 other fieldsHigh correlation
wealth is highly correlated with Open and 14 other fieldsHigh correlation
LogReturn is highly correlated with PriceDiff and 2 other fieldsHigh correlation
df_index is highly correlated with Open and 18 other fieldsHigh correlation
Open is highly correlated with df_index and 20 other fieldsHigh correlation
High is highly correlated with df_index and 20 other fieldsHigh correlation
Low is highly correlated with df_index and 20 other fieldsHigh correlation
Close is highly correlated with df_index and 20 other fieldsHigh correlation
Adj Close is highly correlated with df_index and 20 other fieldsHigh correlation
Volume is highly correlated with df_index and 18 other fieldsHigh correlation
EMA_9 is highly correlated with df_index and 19 other fieldsHigh correlation
EMA_22 is highly correlated with df_index and 19 other fieldsHigh correlation
SMA_5 is highly correlated with df_index and 19 other fieldsHigh correlation
SMA_10 is highly correlated with df_index and 19 other fieldsHigh correlation
SMA_15 is highly correlated with df_index and 19 other fieldsHigh correlation
SMA_30 is highly correlated with df_index and 19 other fieldsHigh correlation
RSI is highly correlated with MACD and 2 other fieldsHigh correlation
MACD is highly correlated with df_index and 22 other fieldsHigh correlation
MACD_signal is highly correlated with df_index and 21 other fieldsHigh correlation
PriceDiff is highly correlated with Open and 10 other fieldsHigh correlation
Return is highly correlated with PriceDiff and 2 other fieldsHigh correlation
ma50 is highly correlated with df_index and 19 other fieldsHigh correlation
MA10 is highly correlated with df_index and 19 other fieldsHigh correlation
MA50 is highly correlated with df_index and 19 other fieldsHigh correlation
Shares is highly correlated with RSI and 3 other fieldsHigh correlation
Close1 is highly correlated with df_index and 20 other fieldsHigh correlation
Profit is highly correlated with Open and 21 other fieldsHigh correlation
wealth is highly correlated with df_index and 20 other fieldsHigh correlation
LogReturn is highly correlated with PriceDiff and 2 other fieldsHigh correlation
df_index is uniformly distributed Uniform
df_index has unique values Unique
Date has unique values Unique
EMA_9 has unique values Unique
EMA_22 has unique values Unique
MACD has unique values Unique
MACD_signal has unique values Unique
Profit has 1030 (43.5%) zeros Zeros

Reproduction

Analysis started2022-06-24 19:04:25.564356
Analysis finished2022-06-24 19:05:09.608706
Duration44.04 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

df_index
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct2366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1231.5
Minimum49
Maximum2414
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:09.668036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum49
5-th percentile167.25
Q1640.25
median1231.5
Q31822.75
95-th percentile2295.75
Maximum2414
Range2365
Interquartile range (IQR)1182.5

Descriptive statistics

Standard deviation683.1496908
Coefficient of variation (CV)0.554729753
Kurtosis-1.2
Mean1231.5
Median Absolute Deviation (MAD)591.5
Skewness0
Sum2913729
Variance466693.5
MonotonicityStrictly increasing
2022-06-24T14:05:09.744923image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
491
 
< 0.1%
16381
 
< 0.1%
16221
 
< 0.1%
16231
 
< 0.1%
16241
 
< 0.1%
16251
 
< 0.1%
16261
 
< 0.1%
16271
 
< 0.1%
16281
 
< 0.1%
16291
 
< 0.1%
Other values (2356)2356
99.6%
ValueCountFrequency (%)
491
< 0.1%
501
< 0.1%
511
< 0.1%
521
< 0.1%
531
< 0.1%
541
< 0.1%
551
< 0.1%
561
< 0.1%
571
< 0.1%
581
< 0.1%
ValueCountFrequency (%)
24141
< 0.1%
24131
< 0.1%
24121
< 0.1%
24111
< 0.1%
24101
< 0.1%
24091
< 0.1%
24081
< 0.1%
24071
< 0.1%
24061
< 0.1%
24051
< 0.1%

Date
Date

UNIQUE

Distinct2366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
Minimum2010-09-08 00:00:00
Maximum2020-01-31 00:00:00
2022-06-24T14:05:09.814415image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:09.882365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Open
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2091
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189.5095521
Minimum19.889999
Maximum640
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:09.955922image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.889999
5-th percentile24.8725005
Q135.284999
median215.4300005
Q3268.737503
95-th percentile352.3899918
Maximum640
Range620.110001
Interquartile range (IQR)233.452504

Descriptive statistics

Standard deviation117.1033283
Coefficient of variation (CV)0.6179283685
Kurtosis-0.7572353672
Mean189.5095521
Median Absolute Deviation (MAD)85.4699935
Skewness-0.06945305606
Sum448379.6002
Variance13713.18951
MonotonicityNot monotonic
2022-06-24T14:05:10.023939image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
306
 
0.3%
286
 
0.3%
2205
 
0.2%
28.55
 
0.2%
33.54
 
0.2%
26.94
 
0.2%
3604
 
0.2%
1504
 
0.2%
2304
 
0.2%
353
 
0.1%
Other values (2081)2321
98.1%
ValueCountFrequency (%)
19.8899991
< 0.1%
19.9500011
< 0.1%
20.161
< 0.1%
20.2000012
0.1%
20.41
< 0.1%
20.432
0.1%
20.4400011
< 0.1%
20.521
< 0.1%
20.5400011
< 0.1%
20.571
< 0.1%
ValueCountFrequency (%)
6401
< 0.1%
632.4199831
< 0.1%
575.6900021
< 0.1%
571.8900151
< 0.1%
570.6300051
< 0.1%
568.489991
< 0.1%
564.251
< 0.1%
544.260011
< 0.1%
541.989991
< 0.1%
530.251
< 0.1%

High
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2090
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.8249112
Minimum20.139999
Maximum653
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:10.094984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20.139999
5-th percentile25.41000025
Q136.01500025
median218.885002
Q3272.4649963
95-th percentile357.1174927
Maximum653
Range632.860001
Interquartile range (IQR)236.449996

Descriptive statistics

Standard deviation119.0439417
Coefficient of variation (CV)0.6173680619
Kurtosis-0.7251669577
Mean192.8249112
Median Absolute Deviation (MAD)87.564995
Skewness-0.06311510107
Sum456223.7398
Variance14171.46005
MonotonicityNot monotonic
2022-06-24T14:05:10.163164image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.57
 
0.3%
307
 
0.3%
287
 
0.3%
276
 
0.3%
34.7999995
 
0.2%
28.54
 
0.2%
29.8899994
 
0.2%
34.4000024
 
0.2%
324
 
0.2%
29.7000014
 
0.2%
Other values (2080)2314
97.8%
ValueCountFrequency (%)
20.1399991
< 0.1%
20.1900011
< 0.1%
20.2800011
< 0.1%
20.411
< 0.1%
20.6399992
0.1%
20.6900011
< 0.1%
20.7000011
< 0.1%
20.751
< 0.1%
20.7900011
< 0.1%
20.8099991
< 0.1%
ValueCountFrequency (%)
6531
< 0.1%
650.8800051
< 0.1%
594.51
< 0.1%
589.7999881
< 0.1%
5821
< 0.1%
576.8099981
< 0.1%
573.8599851
< 0.1%
564.4400021
< 0.1%
548.5800171
< 0.1%
547.4099731
< 0.1%

Low
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2098
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean186.1015469
Minimum19.5
Maximum632.52002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:10.605193image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.5
5-th percentile24.049999
Q134.75749975
median211.0650025
Q3264.1124955
95-th percentile346.1074903
Maximum632.52002
Range613.02002
Interquartile range (IQR)229.3549958

Descriptive statistics

Standard deviation115.2239076
Coefficient of variation (CV)0.6191453512
Kurtosis-0.7615718965
Mean186.1015469
Median Absolute Deviation (MAD)84.1849975
Skewness-0.06712693957
Sum440316.26
Variance13276.54889
MonotonicityNot monotonic
2022-06-24T14:05:10.675926image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.2999996
 
0.3%
286
 
0.3%
2035
 
0.2%
26.54
 
0.2%
2154
 
0.2%
28.5499994
 
0.2%
27.7999994
 
0.2%
29.54
 
0.2%
33.54
 
0.2%
294
 
0.2%
Other values (2088)2321
98.1%
ValueCountFrequency (%)
19.51
< 0.1%
19.651
< 0.1%
19.761
< 0.1%
19.7999992
0.1%
201
< 0.1%
20.0300011
< 0.1%
20.0400011
< 0.1%
20.0499991
< 0.1%
20.071
< 0.1%
20.161
< 0.1%
ValueCountFrequency (%)
632.520021
< 0.1%
6181
< 0.1%
567.4299931
< 0.1%
559.0999761
< 0.1%
558.0800171
< 0.1%
555.5999761
< 0.1%
554.260011
< 0.1%
539.2800291
< 0.1%
528.4099731
< 0.1%
524.9000241
< 0.1%

Close
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2184
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189.6028911
Minimum19.559999
Maximum650.570007
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:10.748772image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.559999
5-th percentile24.75
Q135.32
median215.465004
Q3268.1650088
95-th percentile351.519997
Maximum650.570007
Range631.010008
Interquartile range (IQR)232.8450088

Descriptive statistics

Standard deviation117.2995085
Coefficient of variation (CV)0.6186588604
Kurtosis-0.7254011027
Mean189.6028911
Median Absolute Deviation (MAD)85.580002
Skewness-0.05966702241
Sum448600.4403
Variance13759.1747
MonotonicityNot monotonic
2022-06-24T14:05:10.817202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.424
 
0.2%
33.9000023
 
0.1%
23.253
 
0.1%
32.4599993
 
0.1%
26.53
 
0.1%
31.843
 
0.1%
31.493
 
0.1%
210.0899963
 
0.1%
27.8799993
 
0.1%
26.9599993
 
0.1%
Other values (2174)2335
98.7%
ValueCountFrequency (%)
19.5599991
< 0.1%
19.8700011
< 0.1%
20.0499991
< 0.1%
20.11
< 0.1%
20.171
< 0.1%
20.232
0.1%
20.242
0.1%
20.411
< 0.1%
20.432
0.1%
20.4599991
< 0.1%
ValueCountFrequency (%)
650.5700071
< 0.1%
640.8099981
< 0.1%
580.989991
< 0.1%
572.2000121
< 0.1%
569.5599981
< 0.1%
566.9000241
< 0.1%
564.8200071
< 0.1%
558.020021
< 0.1%
547.2000121
< 0.1%
537.9199831
< 0.1%

Adj Close
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2184
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189.6028911
Minimum19.559999
Maximum650.570007
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:10.888195image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.559999
5-th percentile24.75
Q135.32
median215.465004
Q3268.1650088
95-th percentile351.519997
Maximum650.570007
Range631.010008
Interquartile range (IQR)232.8450088

Descriptive statistics

Standard deviation117.2995085
Coefficient of variation (CV)0.6186588604
Kurtosis-0.7254011027
Mean189.6028911
Median Absolute Deviation (MAD)85.580002
Skewness-0.05966702241
Sum448600.4403
Variance13759.1747
MonotonicityNot monotonic
2022-06-24T14:05:10.956348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.424
 
0.2%
33.9000023
 
0.1%
23.253
 
0.1%
32.4599993
 
0.1%
26.53
 
0.1%
31.843
 
0.1%
31.493
 
0.1%
210.0899963
 
0.1%
27.8799993
 
0.1%
26.9599993
 
0.1%
Other values (2174)2335
98.7%
ValueCountFrequency (%)
19.5599991
< 0.1%
19.8700011
< 0.1%
20.0499991
< 0.1%
20.11
< 0.1%
20.171
< 0.1%
20.232
0.1%
20.242
0.1%
20.411
< 0.1%
20.432
0.1%
20.4599991
< 0.1%
ValueCountFrequency (%)
650.5700071
< 0.1%
640.8099981
< 0.1%
580.989991
< 0.1%
572.2000121
< 0.1%
569.5599981
< 0.1%
566.9000241
< 0.1%
564.8200071
< 0.1%
558.020021
< 0.1%
547.2000121
< 0.1%
537.9199831
< 0.1%

Volume
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2341
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5621049.535
Minimum118500
Maximum37163900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:11.028028image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum118500
5-th percentile659250
Q12018450
median4650500
Q37393575
95-th percentile14749550
Maximum37163900
Range37045400
Interquartile range (IQR)5375125

Descriptive statistics

Standard deviation4915722.537
Coefficient of variation (CV)0.8745204088
Kurtosis6.005680015
Mean5621049.535
Median Absolute Deviation (MAD)2693000
Skewness2.026966731
Sum1.32994032 × 1010
Variance2.416432807 × 1013
MonotonicityNot monotonic
2022-06-24T14:05:11.100518image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32663002
 
0.1%
22226002
 
0.1%
9997002
 
0.1%
32196002
 
0.1%
9863002
 
0.1%
7293002
 
0.1%
11601002
 
0.1%
79950002
 
0.1%
9537002
 
0.1%
56723002
 
0.1%
Other values (2331)2346
99.2%
ValueCountFrequency (%)
1185001
< 0.1%
1410001
< 0.1%
1611001
< 0.1%
1628001
< 0.1%
1712001
< 0.1%
2242001
< 0.1%
2396001
< 0.1%
2440001
< 0.1%
2452001
< 0.1%
2678001
< 0.1%
ValueCountFrequency (%)
371639001
< 0.1%
336497001
< 0.1%
326817001
< 0.1%
323719001
< 0.1%
313690001
< 0.1%
311443001
< 0.1%
310717001
< 0.1%
308758001
< 0.1%
300061001
< 0.1%
297209001
< 0.1%

EMA_9
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct2366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187.3908184
Minimum19.95223772
Maximum531.4156219
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:11.174186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.95223772
5-th percentile24.95603587
Q135.02950885
median217.5087516
Q3267.1492058
95-th percentile343.1525238
Maximum531.4156219
Range511.4633842
Interquartile range (IQR)232.1196969

Descriptive statistics

Standard deviation114.5777265
Coefficient of variation (CV)0.6114372488
Kurtosis-1.112504315
Mean187.3908184
Median Absolute Deviation (MAD)81.69561714
Skewness-0.2000969491
Sum443366.6763
Variance13128.0554
MonotonicityNot monotonic
2022-06-24T14:05:11.249390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.952237721
 
< 0.1%
203.36092631
 
< 0.1%
189.02403041
 
< 0.1%
188.70662791
 
< 0.1%
189.15096451
 
< 0.1%
189.46486741
 
< 0.1%
189.73637991
 
< 0.1%
190.00574131
 
< 0.1%
190.82016651
 
< 0.1%
191.60715011
 
< 0.1%
Other values (2356)2356
99.6%
ValueCountFrequency (%)
19.952237721
< 0.1%
20.047504941
< 0.1%
20.114063071
< 0.1%
20.119680211
< 0.1%
20.179938481
< 0.1%
20.274263691
< 0.1%
20.361978291
< 0.1%
20.37880261
< 0.1%
20.391134141
< 0.1%
20.4453581
< 0.1%
ValueCountFrequency (%)
531.41562191
< 0.1%
519.26069131
< 0.1%
512.40188031
< 0.1%
506.3465311
< 0.1%
500.60503221
< 0.1%
493.4700351
< 0.1%
484.72225981
< 0.1%
475.29584441
< 0.1%
467.30649251
< 0.1%
462.50721391
< 0.1%

EMA_22
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct2366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185.2329488
Minimum19.8277026
Maximum461.2584611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:11.322862image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.8277026
5-th percentile25.23426362
Q133.96091138
median216.7243318
Q3260.8308672
95-th percentile336.2764873
Maximum461.2584611
Range441.4307585
Interquartile range (IQR)226.8699559

Descriptive statistics

Standard deviation112.8901979
Coefficient of variation (CV)0.6094498771
Kurtosis-1.261492465
Mean185.2329488
Median Absolute Deviation (MAD)86.68017076
Skewness-0.2663350512
Sum438261.1569
Variance12744.19678
MonotonicityNot monotonic
2022-06-24T14:05:11.392926image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.82770261
 
< 0.1%
199.08612281
 
< 0.1%
193.96283561
 
< 0.1%
193.61010391
 
< 0.1%
193.59009911
 
< 0.1%
193.53357281
 
< 0.1%
193.47472151
 
< 0.1%
193.42929851
 
< 0.1%
193.63454611
 
< 0.1%
193.85434851
 
< 0.1%
Other values (2356)2356
99.6%
ValueCountFrequency (%)
19.82770261
< 0.1%
19.879988241
< 0.1%
19.920247241
< 0.1%
19.932300721
< 0.1%
19.970135341
< 0.1%
20.025115191
< 0.1%
20.118182811
< 0.1%
20.157146811
< 0.1%
20.160587381
< 0.1%
20.178476331
< 0.1%
ValueCountFrequency (%)
461.25846111
< 0.1%
453.09702761
< 0.1%
447.28371111
< 0.1%
441.8466061
< 0.1%
436.56599631
< 0.1%
430.73626851
< 0.1%
424.30609841
< 0.1%
417.70364841
< 0.1%
411.817451
< 0.1%
407.33187961
< 0.1%

SMA_5
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2357
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188.8471497
Minimum20.1660002
Maximum582.3080078
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:11.463237image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20.1660002
5-th percentile24.75000025
Q135.34250045
median215.5419998
Q3269.5650093
95-th percentile349.533998
Maximum582.3080078
Range562.1420076
Interquartile range (IQR)234.2225088

Descriptive statistics

Standard deviation116.3061465
Coefficient of variation (CV)0.6158745138
Kurtosis-0.9074756951
Mean188.8471497
Median Absolute Deviation (MAD)86.0309952
Skewness-0.1166701007
Sum446812.3563
Variance13527.11972
MonotonicityNot monotonic
2022-06-24T14:05:11.531344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230.68199782
 
0.1%
218.53999942
 
0.1%
28.6462
 
0.1%
34.1822
 
0.1%
227.33799742
 
0.1%
28.80399962
 
0.1%
28.272
 
0.1%
20.4442
 
0.1%
229.67999582
 
0.1%
203.85799861
 
< 0.1%
Other values (2347)2347
99.2%
ValueCountFrequency (%)
20.16600021
< 0.1%
20.27199981
< 0.1%
20.29200021
< 0.1%
20.29799981
< 0.1%
20.35999981
< 0.1%
20.37600021
< 0.1%
20.42200021
< 0.1%
20.44000021
< 0.1%
20.4442
0.1%
20.46000041
< 0.1%
ValueCountFrequency (%)
582.30800781
< 0.1%
568.58601061
< 0.1%
566.30001221
< 0.1%
562.36000981
< 0.1%
552.85600581
< 0.1%
542.59000241
< 0.1%
531.851
< 0.1%
525.5219971
< 0.1%
521.05399161
< 0.1%
514.58399041
< 0.1%

SMA_10
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2358
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188.2696683
Minimum20.1000003
Maximum562.4490051
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:11.601945image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20.1000003
5-th percentile24.8157497
Q135.4535007
median215.5784989
Q3269.1400063
95-th percentile347.9527529
Maximum562.4490051
Range542.3490048
Interquartile range (IQR)233.6865056

Descriptive statistics

Standard deviation115.627958
Coefficient of variation (CV)0.6141613731
Kurtosis-1.00109951
Mean188.2696683
Median Absolute Deviation (MAD)85.35950125
Skewness-0.151437585
Sum445446.0353
Variance13369.82467
MonotonicityNot monotonic
2022-06-24T14:05:11.676767image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.64400013
 
0.1%
29.08599992
 
0.1%
29.852
 
0.1%
20.692
 
0.1%
22.69999992
 
0.1%
28.11200022
 
0.1%
27.31500052
 
0.1%
195.55399781
 
< 0.1%
189.35999761
 
< 0.1%
190.28899841
 
< 0.1%
Other values (2348)2348
99.2%
ValueCountFrequency (%)
20.10000031
< 0.1%
20.27000021
< 0.1%
20.35100011
< 0.1%
20.3911
< 0.1%
20.39300011
< 0.1%
20.41000011
< 0.1%
20.44200011
< 0.1%
20.4711
< 0.1%
20.49499991
< 0.1%
20.49800021
< 0.1%
ValueCountFrequency (%)
562.44900511
< 0.1%
550.21800531
< 0.1%
545.91100461
< 0.1%
541.70700071
< 0.1%
533.71999811
< 0.1%
525.3719971
< 0.1%
517.36599731
< 0.1%
507.31599731
< 0.1%
497.7499971
< 0.1%
491.0009981
< 0.1%

SMA_15
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2365
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187.7195473
Minimum19.7960002
Maximum544.3506673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:11.747509image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.7960002
5-th percentile24.66833313
Q135.3511669
median215.9653336
Q3267.818836
95-th percentile346.3631694
Maximum544.3506673
Range524.5546671
Interquartile range (IQR)232.4676691

Descriptive statistics

Standard deviation115.0311458
Coefficient of variation (CV)0.6127819262
Kurtosis-1.078100094
Mean187.7195473
Median Absolute Deviation (MAD)84.8153336
Skewness-0.1810959444
Sum444144.4489
Variance13232.1645
MonotonicityNot monotonic
2022-06-24T14:05:11.822413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.41599932
 
0.1%
19.79600021
 
< 0.1%
191.18466491
 
< 0.1%
187.57000011
 
< 0.1%
187.86333411
 
< 0.1%
188.48866671
 
< 0.1%
189.04600011
 
< 0.1%
189.2806661
 
< 0.1%
189.77466531
 
< 0.1%
190.68333131
 
< 0.1%
Other values (2355)2355
99.5%
ValueCountFrequency (%)
19.79600021
< 0.1%
19.912666871
< 0.1%
20.042000131
< 0.1%
20.134000071
< 0.1%
20.2421
< 0.1%
20.308000131
< 0.1%
20.49333341
< 0.1%
20.512000071
< 0.1%
20.533333331
< 0.1%
20.534666731
< 0.1%
ValueCountFrequency (%)
544.35066731
< 0.1%
534.43933511
< 0.1%
526.97733561
< 0.1%
519.28666791
< 0.1%
511.61933391
< 0.1%
502.64866751
< 0.1%
492.39066581
< 0.1%
482.06666671
< 0.1%
474.27866631
< 0.1%
468.97466641
< 0.1%

SMA_30
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2365
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean186.2386728
Minimum19.79666687
Maximum485.7286682
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:11.893235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.79666687
5-th percentile24.64133321
Q134.89941703
median216.2111654
Q3265.3990007
95-th percentile343.7774162
Maximum485.7286682
Range465.9320014
Interquartile range (IQR)230.4995836

Descriptive statistics

Standard deviation113.7092129
Coefficient of variation (CV)0.6105563962
Kurtosis-1.220187561
Mean186.2386728
Median Absolute Deviation (MAD)84.52833345
Skewness-0.2400790306
Sum440640.6999
Variance12929.7851
MonotonicityNot monotonic
2022-06-24T14:05:11.967245image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.369333472
 
0.1%
189.79899951
 
< 0.1%
190.48666681
 
< 0.1%
190.18033341
 
< 0.1%
189.84866641
 
< 0.1%
189.4543331
 
< 0.1%
189.20299941
 
< 0.1%
189.21699931
 
< 0.1%
189.48033291
 
< 0.1%
19.796666871
 
< 0.1%
Other values (2355)2355
99.5%
ValueCountFrequency (%)
19.796666871
< 0.1%
19.802000231
< 0.1%
19.808000231
< 0.1%
19.808333571
< 0.1%
19.817666831
< 0.1%
19.82500021
< 0.1%
19.828000171
< 0.1%
19.834666871
< 0.1%
19.835666831
< 0.1%
19.86666681
< 0.1%
ValueCountFrequency (%)
485.72866821
< 0.1%
477.08500161
< 0.1%
469.66500251
< 0.1%
462.75766811
< 0.1%
455.91366781
< 0.1%
448.71433411
< 0.1%
440.9586671
< 0.1%
433.16966761
< 0.1%
425.94200041
< 0.1%
420.02633371
< 0.1%

RSI
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2365
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.41638976
Minimum5.139192883
Maximum96.48702173
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:12.038742image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5.139192883
5-th percentile24.58221055
Q140.71534691
median53.45777919
Q365.92686048
95-th percentile81.91899831
Maximum96.48702173
Range91.34782884
Interquartile range (IQR)25.21151356

Descriptive statistics

Standard deviation17.31683346
Coefficient of variation (CV)0.3241857702
Kurtosis-0.5836562365
Mean53.41638976
Median Absolute Deviation (MAD)12.62923948
Skewness-0.01001788646
Sum126383.1782
Variance299.872721
MonotonicityNot monotonic
2022-06-24T14:05:12.108445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45.423719622
 
0.1%
67.149780551
 
< 0.1%
57.632411831
 
< 0.1%
53.955100561
 
< 0.1%
58.451362021
 
< 0.1%
59.39206181
 
< 0.1%
58.474987531
 
< 0.1%
56.981138481
 
< 0.1%
51.244990961
 
< 0.1%
68.577061141
 
< 0.1%
Other values (2355)2355
99.5%
ValueCountFrequency (%)
5.1391928831
< 0.1%
8.3040220821
< 0.1%
9.8197443751
< 0.1%
9.9715582141
< 0.1%
10.054490411
< 0.1%
10.484449951
< 0.1%
10.720955971
< 0.1%
10.821709581
< 0.1%
10.972742111
< 0.1%
11.09995611
< 0.1%
ValueCountFrequency (%)
96.487021731
< 0.1%
95.775616041
< 0.1%
93.855818031
< 0.1%
92.74029431
< 0.1%
92.565367541
< 0.1%
92.078965441
< 0.1%
91.782905591
< 0.1%
91.521139841
< 0.1%
91.415476011
< 0.1%
91.051930851
< 0.1%

MACD
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct2366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.35385321
Minimum-18.8518728
Maximum53.24119947
Zeros0
Zeros (%)0.0%
Negative1040
Negative (%)44.0%
Memory size18.6 KiB
2022-06-24T14:05:12.178132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-18.8518728
5-th percentile-8.882139464
Q1-2.238874557
median0.3294545907
Q34.162748631
95-th percentile12.94405529
Maximum53.24119947
Range72.09307227
Interquartile range (IQR)6.401623187

Descriptive statistics

Standard deviation7.381338981
Coefficient of variation (CV)5.452096967
Kurtosis6.975891862
Mean1.35385321
Median Absolute Deviation (MAD)3.075705825
Skewness1.544114853
Sum3203.216695
Variance54.48416515
MonotonicityNot monotonic
2022-06-24T14:05:12.247886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2873146221
 
< 0.1%
6.5726268391
 
< 0.1%
-2.4532786641
 
< 0.1%
-1.8236877511
 
< 0.1%
-1.3782398191
 
< 0.1%
-1.0223106441
 
< 0.1%
-0.71185547031
 
< 0.1%
-0.0042126710471
 
< 0.1%
0.59333389441
 
< 0.1%
0.96618850961
 
< 0.1%
Other values (2356)2356
99.6%
ValueCountFrequency (%)
-18.85187281
< 0.1%
-18.50449011
< 0.1%
-18.48645131
< 0.1%
-18.38140161
< 0.1%
-18.291517461
< 0.1%
-18.0777161
< 0.1%
-18.024584541
< 0.1%
-17.756269621
< 0.1%
-17.42376951
< 0.1%
-17.287754681
< 0.1%
ValueCountFrequency (%)
53.241199471
< 0.1%
49.540462571
< 0.1%
46.157902471
< 0.1%
45.871275391
< 0.1%
45.314002771
< 0.1%
45.090134391
< 0.1%
44.844805281
< 0.1%
44.086797761
< 0.1%
41.436694311
< 0.1%
41.058174041
< 0.1%

MACD_signal
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct2366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.275839043
Minimum-17.11594494
Maximum46.19932641
Zeros0
Zeros (%)0.0%
Negative1029
Negative (%)43.5%
Memory size18.6 KiB
2022-06-24T14:05:12.320484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-17.11594494
5-th percentile-8.342053504
Q1-2.186076877
median0.2745943364
Q33.984052993
95-th percentile11.98994498
Maximum46.19932641
Range63.31527135
Interquartile range (IQR)6.17012987

Descriptive statistics

Standard deviation6.742438161
Coefficient of variation (CV)5.284709068
Kurtosis6.102146188
Mean1.275839043
Median Absolute Deviation (MAD)2.927436352
Skewness1.436196944
Sum3018.635176
Variance45.46047236
MonotonicityNot monotonic
2022-06-24T14:05:12.388371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.10029261341
 
< 0.1%
4.3720995051
 
< 0.1%
-2.4738274351
 
< 0.1%
-2.3437994981
 
< 0.1%
-2.1506875631
 
< 0.1%
-1.9250121791
 
< 0.1%
-1.6823808371
 
< 0.1%
-1.3467472041
 
< 0.1%
-0.95873098421
 
< 0.1%
-0.57374708551
 
< 0.1%
Other values (2356)2356
99.6%
ValueCountFrequency (%)
-17.115944941
< 0.1%
-16.984160491
< 0.1%
-16.955863771
< 0.1%
-16.4883051
< 0.1%
-16.481861521
< 0.1%
-15.980714071
< 0.1%
-15.775804061
< 0.1%
-15.380542191
< 0.1%
-14.822658491
< 0.1%
-14.79521011
< 0.1%
ValueCountFrequency (%)
46.199326411
< 0.1%
44.438858141
< 0.1%
43.163457031
< 0.1%
42.68178771
< 0.1%
42.14103331
< 0.1%
41.347790941
< 0.1%
40.145263051
< 0.1%
38.713759971
< 0.1%
37.370500521
< 0.1%
36.353952071
< 0.1%

PriceDiff
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2097
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3208368555
Minimum-45.049988
Maximum129.429993
Zeros9
Zeros (%)0.4%
Negative1145
Negative (%)48.4%
Memory size18.6 KiB
2022-06-24T14:05:12.459345image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-45.049988
5-th percentile-9.7475045
Q1-1.73000825
median0.080002
Q32.440002
95-th percentile9.9250105
Maximum129.429993
Range174.479981
Interquartile range (IQR)4.17001025

Descriptive statistics

Standard deviation7.135986873
Coefficient of variation (CV)22.24179284
Kurtosis53.27331129
Mean0.3208368555
Median Absolute Deviation (MAD)2.0900035
Skewness3.011584032
Sum759.1
Variance50.92230866
MonotonicityNot monotonic
2022-06-24T14:05:12.531580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09
 
0.4%
-0.57
 
0.3%
0.57
 
0.3%
16
 
0.3%
0.756
 
0.3%
0.245
 
0.2%
-0.255
 
0.2%
-0.184
 
0.2%
0.594
 
0.2%
0.2099994
 
0.2%
Other values (2087)2309
97.6%
ValueCountFrequency (%)
-45.0499881
< 0.1%
-42.751
< 0.1%
-36.0599981
< 0.1%
-29.9500121
< 0.1%
-29.7699891
< 0.1%
-25.6499941
< 0.1%
-25.5299991
< 0.1%
-25.3400111
< 0.1%
-25.0899961
< 0.1%
-251
< 0.1%
ValueCountFrequency (%)
129.4299931
< 0.1%
59.8200081
< 0.1%
48.7000131
< 0.1%
46.7099911
< 0.1%
45.9300231
< 0.1%
451
< 0.1%
37.5800171
< 0.1%
36.7000121
< 0.1%
33.1900031
< 0.1%
30.6999811
< 0.1%

Return
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2358
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002047957066
Minimum-0.1932743009
Maximum0.2439505423
Zeros9
Zeros (%)0.4%
Negative1145
Negative (%)48.4%
Memory size18.6 KiB
2022-06-24T14:05:12.607996image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-0.1932743009
5-th percentile-0.04565921799
Q1-0.01394756343
median0.0009012674855
Q30.01800826745
95-th percentile0.04802619314
Maximum0.2439505423
Range0.4372248432
Interquartile range (IQR)0.03195583089

Descriptive statistics

Standard deviation0.03235681023
Coefficient of variation (CV)15.79955496
Kurtosis6.652882366
Mean0.002047957066
Median Absolute Deviation (MAD)0.01613190103
Skewness0.674968629
Sum4.845466418
Variance0.001046963168
MonotonicityNot monotonic
2022-06-24T14:05:12.678980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09
 
0.4%
-0.0090909569381
 
< 0.1%
-0.00057205264971
 
< 0.1%
0.029725101121
 
< 0.1%
0.0027252486321
 
< 0.1%
-0.0055865921231
 
< 0.1%
0.024850708321
 
< 0.1%
0.001185199241
 
< 0.1%
0.029891960341
 
< 0.1%
-0.0052205375571
 
< 0.1%
Other values (2348)2348
99.2%
ValueCountFrequency (%)
-0.19327430091
< 0.1%
-0.15088072451
< 0.1%
-0.14507094791
< 0.1%
-0.14309287061
< 0.1%
-0.13901535361
< 0.1%
-0.13613710861
< 0.1%
-0.12971117521
< 0.1%
-0.11303704651
< 0.1%
-0.10450342381
< 0.1%
-0.10239937471
< 0.1%
ValueCountFrequency (%)
0.24395054231
< 0.1%
0.19894860141
< 0.1%
0.19204231391
< 0.1%
0.17669232461
< 0.1%
0.17347140881
< 0.1%
0.17039228891
< 0.1%
0.16717853591
< 0.1%
0.16533783791
< 0.1%
0.16188011451
< 0.1%
0.15940884561
< 0.1%

ma50
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2364
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184.7651826
Minimum19.67200002
Maximum435.1906018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:12.751450image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.67200002
5-th percentile25.07684992
Q134.29105024
median216.796099
Q3261.2355024
95-th percentile340.517099
Maximum435.1906018
Range415.5186018
Interquartile range (IQR)226.9444521

Descriptive statistics

Standard deviation112.7943303
Coefficient of variation (CV)0.6104739468
Kurtosis-1.284290062
Mean184.7651826
Median Absolute Deviation (MAD)86.35540173
Skewness-0.2698955148
Sum437154.422
Variance12722.56094
MonotonicityNot monotonic
2022-06-24T14:05:12.821020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.181200142
 
0.1%
233.09439942
 
0.1%
193.70879981
 
< 0.1%
195.20940041
 
< 0.1%
194.95620031
 
< 0.1%
194.67660011
 
< 0.1%
194.50621
 
< 0.1%
194.27419991
 
< 0.1%
193.96319981
 
< 0.1%
193.49119971
 
< 0.1%
Other values (2354)2354
99.5%
ValueCountFrequency (%)
19.672000021
< 0.1%
19.696800021
< 0.1%
19.710400021
< 0.1%
19.770000021
< 0.1%
19.82781
< 0.1%
19.833600021
< 0.1%
19.930600021
< 0.1%
19.986000041
< 0.1%
20.059200021
< 0.1%
20.129200141
< 0.1%
ValueCountFrequency (%)
435.19060181
< 0.1%
429.17900151
< 0.1%
423.40620181
< 0.1%
418.77340211
< 0.1%
414.35760131
< 0.1%
410.19580081
< 0.1%
405.80120061
< 0.1%
401.10000061
< 0.1%
396.41960081
< 0.1%
392.00720031
< 0.1%

MA10
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2358
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188.5046882
Minimum20.2700002
Maximum576.1570068
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:12.891259image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20.2700002
5-th percentile24.83474987
Q135.4732506
median215.7884988
Q3269.4687538
95-th percentile348.1804955
Maximum576.1570068
Range555.8870066
Interquartile range (IQR)233.9955032

Descriptive statistics

Standard deviation115.8508924
Coefficient of variation (CV)0.6145783084
Kurtosis-0.9639721548
Mean188.5046882
Median Absolute Deviation (MAD)85.35950125
Skewness-0.1394778517
Sum446002.0923
Variance13421.42927
MonotonicityNot monotonic
2022-06-24T14:05:12.959490image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.64400013
 
0.1%
29.852
 
0.1%
29.08599992
 
0.1%
22.69999992
 
0.1%
28.11200022
 
0.1%
20.692
 
0.1%
27.31500052
 
0.1%
199.30299681
 
< 0.1%
190.28899841
 
< 0.1%
191.85899811
 
< 0.1%
Other values (2348)2348
99.2%
ValueCountFrequency (%)
20.27000021
< 0.1%
20.35100011
< 0.1%
20.3911
< 0.1%
20.39300011
< 0.1%
20.41000011
< 0.1%
20.44200011
< 0.1%
20.4711
< 0.1%
20.49499991
< 0.1%
20.49800021
< 0.1%
20.5321
< 0.1%
ValueCountFrequency (%)
576.15700681
< 0.1%
562.44900511
< 0.1%
550.21800531
< 0.1%
545.91100461
< 0.1%
541.70700071
< 0.1%
533.71999811
< 0.1%
525.3719971
< 0.1%
517.36599731
< 0.1%
507.31599731
< 0.1%
497.7499971
< 0.1%

MA50
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2364
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184.7651826
Minimum19.67200002
Maximum435.1906018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:13.032036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.67200002
5-th percentile25.07684992
Q134.29105024
median216.796099
Q3261.2355024
95-th percentile340.517099
Maximum435.1906018
Range415.5186018
Interquartile range (IQR)226.9444521

Descriptive statistics

Standard deviation112.7943303
Coefficient of variation (CV)0.6104739468
Kurtosis-1.284290062
Mean184.7651826
Median Absolute Deviation (MAD)86.35540173
Skewness-0.2698955148
Sum437154.422
Variance12722.56094
MonotonicityNot monotonic
2022-06-24T14:05:13.101742image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.181200142
 
0.1%
233.09439942
 
0.1%
193.70879981
 
< 0.1%
195.20940041
 
< 0.1%
194.95620031
 
< 0.1%
194.67660011
 
< 0.1%
194.50621
 
< 0.1%
194.27419991
 
< 0.1%
193.96319981
 
< 0.1%
193.49119971
 
< 0.1%
Other values (2354)2354
99.5%
ValueCountFrequency (%)
19.672000021
< 0.1%
19.696800021
< 0.1%
19.710400021
< 0.1%
19.770000021
< 0.1%
19.82781
< 0.1%
19.833600021
< 0.1%
19.930600021
< 0.1%
19.986000041
< 0.1%
20.059200021
< 0.1%
20.129200141
< 0.1%
ValueCountFrequency (%)
435.19060181
< 0.1%
429.17900151
< 0.1%
423.40620181
< 0.1%
418.77340211
< 0.1%
414.35760131
< 0.1%
410.19580081
< 0.1%
405.80120061
< 0.1%
401.10000061
< 0.1%
396.41960081
< 0.1%
392.00720031
< 0.1%

Shares
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
1
1340 
0
1026 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2366
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
11340
56.6%
01026
43.4%

Length

2022-06-24T14:05:13.162213image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-24T14:05:13.254752image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
11340
56.6%
01026
43.4%

Most occurring characters

ValueCountFrequency (%)
11340
56.6%
01026
43.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2366
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
11340
56.6%
01026
43.4%

Most occurring scripts

ValueCountFrequency (%)
Common2366
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
11340
56.6%
01026
43.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII2366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11340
56.6%
01026
43.4%

Close1
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2183
Distinct (%)92.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean189.6742242
Minimum19.559999
Maximum650.570007
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2022-06-24T14:05:13.327204image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19.559999
5-th percentile24.764
Q135.32
median215.470001
Q3268.26001
95-th percentile351.5279972
Maximum650.570007
Range631.010008
Interquartile range (IQR)232.94001

Descriptive statistics

Standard deviation117.2729752
Coefficient of variation (CV)0.6182863045
Kurtosis-0.7240443371
Mean189.6742242
Median Absolute Deviation (MAD)85.570007
Skewness-0.06029879437
Sum448579.5403
Variance13752.9507
MonotonicityNot monotonic
2022-06-24T14:05:13.395187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.424
 
0.2%
27.1200013
 
0.1%
34.4000023
 
0.1%
26.63
 
0.1%
32.4599993
 
0.1%
210.0899963
 
0.1%
28.173
 
0.1%
27.8799993
 
0.1%
27.573
 
0.1%
30.663
 
0.1%
Other values (2173)2334
98.6%
ValueCountFrequency (%)
19.5599991
< 0.1%
19.8700011
< 0.1%
20.0499991
< 0.1%
20.11
< 0.1%
20.171
< 0.1%
20.232
0.1%
20.242
0.1%
20.411
< 0.1%
20.432
0.1%
20.4599991
< 0.1%
ValueCountFrequency (%)
650.5700071
< 0.1%
640.8099981
< 0.1%
580.989991
< 0.1%
572.2000121
< 0.1%
569.5599981
< 0.1%
566.9000241
< 0.1%
564.8200071
< 0.1%
558.020021
< 0.1%
547.2000121
< 0.1%
537.9199831
< 0.1%

Profit
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct1232
Distinct (%)52.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.2238139497
Minimum-36.059998
Maximum59.820008
Zeros1030
Zeros (%)43.5%
Negative643
Negative (%)27.2%
Memory size18.6 KiB
2022-06-24T14:05:13.466747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-36.059998
5-th percentile-6.2580014
Q1-0.170013
median0
Q30.430001
95-th percentile7.2200074
Maximum59.820008
Range95.880006
Interquartile range (IQR)0.600014

Descriptive statistics

Standard deviation4.827808553
Coefficient of variation (CV)21.57063293
Kurtosis25.88411032
Mean0.2238139497
Median Absolute Deviation (MAD)0.27
Skewness1.438784332
Sum529.319991
Variance23.30773543
MonotonicityNot monotonic
2022-06-24T14:05:13.540723image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01030
43.5%
0.754
 
0.2%
-0.184
 
0.2%
-0.254
 
0.2%
-0.54
 
0.2%
0.54
 
0.2%
2.4400023
 
0.1%
-0.753
 
0.1%
0.593
 
0.1%
0.2099993
 
0.1%
Other values (1222)1303
55.1%
ValueCountFrequency (%)
-36.0599981
< 0.1%
-29.9500121
< 0.1%
-29.7699891
< 0.1%
-25.5299991
< 0.1%
-25.3400111
< 0.1%
-24.3799741
< 0.1%
-24.2100221
< 0.1%
-241
< 0.1%
-21.7899781
< 0.1%
-19.4199831
< 0.1%
ValueCountFrequency (%)
59.8200081
< 0.1%
46.7099911
< 0.1%
451
< 0.1%
36.7000121
< 0.1%
30.6999811
< 0.1%
30.3500061
< 0.1%
28.4500121
< 0.1%
23.1099851
< 0.1%
23.0800171
< 0.1%
22.3599861
< 0.1%

wealth
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1306
Distinct (%)55.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean130.4019829
Minimum-2.259998
Maximum529.319991
Zeros0
Zeros (%)0.0%
Negative74
Negative (%)3.1%
Memory size18.6 KiB
2022-06-24T14:05:13.610982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-2.259998
5-th percentile1.100001
Q19.690004
median144.599975
Q3200.309982
95-th percentile249.9179712
Maximum529.319991
Range531.579989
Interquartile range (IQR)190.619978

Descriptive statistics

Standard deviation91.37545034
Coefficient of variation (CV)0.7007213258
Kurtosis-0.5040275102
Mean130.4019829
Median Absolute Deviation (MAD)65.349991
Skewness-0.0450231611
Sum308400.6896
Variance8349.472925
MonotonicityNot monotonic
2022-06-24T14:05:13.684027image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.37999127
 
5.4%
144.59997576
 
3.2%
5.7762
 
2.6%
212.73997560
 
2.5%
244.87998954
 
2.3%
7.54000249
 
2.1%
143.14997947
 
2.0%
180.78999147
 
2.0%
155.11997945
 
1.9%
116.85000340
 
1.7%
Other values (1296)1758
74.3%
ValueCountFrequency (%)
-2.2599981
< 0.1%
-2.1399991
< 0.1%
-2.1300011
< 0.1%
-1.8699981
< 0.1%
-1.6300011
< 0.1%
-1.3800011
< 0.1%
-1.3400011
< 0.1%
-1.3099991
< 0.1%
-1.271
< 0.1%
-1.1400021
< 0.1%
ValueCountFrequency (%)
529.3199911
< 0.1%
519.5599821
< 0.1%
459.7399741
< 0.1%
450.9499961
< 0.1%
448.3099821
< 0.1%
445.6500081
< 0.1%
443.5699911
< 0.1%
436.7700041
< 0.1%
425.9499961
< 0.1%
416.6699671
< 0.1%

LogReturn
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2357
Distinct (%)99.7%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.001453741968
Minimum-0.2147715705
Maximum0.2182922365
Zeros9
Zeros (%)0.4%
Negative1145
Negative (%)48.4%
Memory size18.6 KiB
2022-06-24T14:05:13.756220image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-0.2147715705
5-th percentile-0.04674164143
Q1-0.01404889345
median0.0009008108717
Q30.01781017703
95-th percentile0.04681503247
Maximum0.2182922365
Range0.433063807
Interquartile range (IQR)0.03185907048

Descriptive statistics

Standard deviation0.03186742826
Coefficient of variation (CV)21.92096601
Kurtosis5.789235447
Mean0.001453741968
Median Absolute Deviation (MAD)0.01606038084
Skewness0.228439087
Sum3.438099753
Variance0.001015532984
MonotonicityNot monotonic
2022-06-24T14:05:13.828333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09
 
0.4%
-0.0091325318491
 
< 0.1%
-0.00057221633421
 
< 0.1%
0.02929187451
 
< 0.1%
0.0027215418751
 
< 0.1%
-0.0056022554921
 
< 0.1%
0.024546951561
 
< 0.1%
0.0011844974461
 
< 0.1%
0.029453903871
 
< 0.1%
-0.0052342121771
 
< 0.1%
Other values (2347)2347
99.2%
ValueCountFrequency (%)
-0.21477157051
< 0.1%
-0.16355561311
< 0.1%
-0.15673679341
< 0.1%
-0.15442573341
< 0.1%
-0.1496786071
< 0.1%
-0.14634121331
< 0.1%
-0.13893013991
< 0.1%
-0.11995206371
< 0.1%
-0.11037688081
< 0.1%
-0.10803004761
< 0.1%
ValueCountFrequency (%)
0.21829223651
< 0.1%
0.17566806631
< 0.1%
0.16270738771
< 0.1%
0.1599663721
< 0.1%
0.15733898231
< 0.1%
0.15458932871
< 0.1%
0.15301103461
< 0.1%
0.15003948141
< 0.1%
0.14791025931
< 0.1%
0.14616304291
< 0.1%

Interactions

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2022-06-24T14:04:49.787923image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:51.287445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:53.108535image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:54.689342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:56.283634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:57.804497image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:59.302735image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:01.156893image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:02.652390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:04.209200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:05.738945image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:07.269698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:08.851748image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:29.537615image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:31.121461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:32.710789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:34.296950image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:35.876058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:38.644617image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:40.270992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:41.983892image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:43.486038image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:45.041605image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:46.791090image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:48.318588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:49.847515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:51.347088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:53.170533image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:54.751880image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:56.343906image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:57.864649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:04:59.361359image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:01.216843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:02.710829image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:04.270759image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:05.799928image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-06-24T14:05:07.331186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-06-24T14:05:13.931282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-06-24T14:05:14.324944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-06-24T14:05:14.719880image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-06-24T14:05:15.113277image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-06-24T14:05:08.998530image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2022-06-24T14:05:09.352053image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-06-24T14:05:09.461416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-06-24T14:05:09.535477image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

df_indexDateOpenHighLowCloseAdj CloseVolumeEMA_9EMA_22SMA_5SMA_10SMA_15SMA_30RSIMACDMACD_signalPriceDiffReturnma50MA10MA50SharesClose1ProfitwealthLogReturn
0492010-09-0820.66000020.95000120.60000020.90000020.90000028840019.95223819.82770320.51620.10019.79600019.79666767.1497810.2873150.100293-0.190001-0.00909119.833620.27019.8336120.709999-0.190001-0.190001-0.009133
1502010-09-0921.00000021.04999920.69000120.70999920.70999937620020.04750519.87998820.80020.27019.91266719.80833465.0470250.3019010.140736-0.539999-0.02607419.770020.35119.7700120.170000-0.539999-0.730000-0.026420
2512010-09-1020.75000020.93000019.76000020.17000020.17000038660020.11406319.92024720.85220.35120.04200019.80800058.0938070.2675300.1661570.5499990.02726819.696820.39319.6968120.7199990.549999-0.1800010.026903
3522010-09-1320.88999920.90000020.50000020.71999920.71999936080020.11968019.93230120.67420.39320.13400019.80200054.8124040.2807360.1891170.4000020.01930519.672020.49519.6720121.1200010.4000020.2200010.019121
4532010-09-1420.54000121.60000020.53000121.12000121.12000165470020.17993819.97013520.60820.49520.24200019.82800067.1428690.3193190.2151980.8599990.04072019.710420.62019.7104121.9800000.8599991.0800000.039912
5542010-09-1520.98000022.00000020.79000121.98000021.98000068460020.27426420.02511520.72420.62020.30800019.83466768.0555680.4135730.254922-1.039999-0.04731619.827820.87019.8278120.940001-1.0399990.040001-0.048472
6552010-09-1622.15000023.16000020.84000020.94000120.940001268450020.44535820.11818320.94020.87020.49333319.83566758.9473830.4007560.284118-0.710001-0.03390619.930620.91919.9306120.230000-0.710001-0.670000-0.034495
7562010-09-1721.02000021.32000019.79999920.23000020.230000119850020.49495820.15714720.98620.91920.56266719.82500053.6251660.3301560.2933330.8299990.04102819.986020.83619.9860121.0599990.8299990.1599990.040209
8572010-09-2020.67000021.35000020.16000021.05999921.05999994750020.46839720.16058720.99820.83620.59466719.81766757.4654870.3365850.301988-0.289999-0.01377020.059220.83720.0592120.770000-0.289999-0.130000-0.013866
9582010-09-2120.88999921.54999920.67000020.77000020.77000079600020.52768920.20290521.06620.83720.68533319.86666758.1956860.3148740.304567-0.899999-0.04333220.133620.86020.1336119.870001-0.899999-1.029999-0.044299

Last rows

df_indexDateOpenHighLowCloseAdj CloseVolumeEMA_9EMA_22SMA_5SMA_10SMA_15SMA_30RSIMACDMACD_signalPriceDiffReturnma50MA10MA50SharesClose1ProfitwealthLogReturn
235624052020-01-17507.609985515.669983503.160004510.500000510.50000013629100462.507214407.331880514.583990491.000998468.974666420.02633470.61760239.72813636.35395236.7000120.071890392.007200497.749997392.0072001547.20001236.700012425.9499960.069424
235724062020-01-21530.250000548.580017528.409973547.200012547.20001217803500467.306492411.817450521.053992497.749997474.278666425.94200080.76815841.43669437.37050122.3599860.040863396.419601507.315997396.4196011569.55999822.359986448.3099820.040050
235824072020-01-22571.890015594.500000559.099976569.559998569.55999831369000475.295844417.703648525.521997507.315997482.066667433.16966882.30719944.08679838.7137602.6400140.004635401.100001517.365997401.1000011572.2000122.640014450.9499960.004624
235924082020-01-23564.250000582.000000555.599976572.200012572.20001219651000484.722260424.306098531.850000517.365997492.390666440.95866781.57590245.87127540.145263-7.380005-0.012898405.801201525.371997405.8012011564.820007-7.380005443.569991-0.012981
236024092020-01-24570.630005573.859985554.260010564.820007564.82000714353600493.470035430.736269542.590002525.371997502.648667448.71433477.76106246.15790241.347791-6.799987-0.012039410.195801533.719998410.1958011558.020020-6.799987436.770004-0.012112
236124102020-01-27541.989990564.440002539.280029558.020020558.02002013608100500.605032436.565996552.856006533.719998511.619334455.91366874.46016945.31400342.1410338.8800040.015913414.357601541.707001414.3576011566.9000248.880004445.6500080.015788
236224112020-01-28568.489990576.809998558.080017566.900024566.90002411788500506.346531441.846606562.360010541.707001519.286668462.75766873.40446344.84480542.68178814.0899660.024854418.773402545.911005418.7734021580.98999014.089966459.7399740.024551
236324122020-01-29575.690002589.799988567.429993580.989990580.98999017801500512.401880447.283711566.300012545.911005526.977336469.66500272.20916645.09013443.16345759.8200080.102962423.406202550.218005423.4062021640.80999859.820008519.5599820.097999
236424132020-01-30632.419983650.880005618.000000640.809998640.80999829005700519.260691453.097028568.586011550.218005534.439335477.08500282.01566649.54046344.4388589.7600090.015231429.179001562.449005429.1790011650.5700079.760009529.3199910.015116
236524142020-01-31640.000000653.000000632.520020650.570007650.57000715719300531.415622461.258461582.308008562.449005544.350667485.72866883.72585053.24119946.199326129.4299930.198949435.190602576.157007435.1906021NaNNaNNaNNaN